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Automated analysis of mammographic densities
Open accessAbstract
Information derived from mammographic parenchymal patterns provides one of the strongest indicators of the risk of developing breast cancer. To address several limitations of subjective classification of mammographic parenchyma into coarse density categories, we have been investigating more quantitative, objective methods of analysing the film-screen mammogram. These include measures of the skewness of the image brightness histogram, and of image texture characterized by the fractal dimension. Both measures were found to be strongly correlated with radiologists' subjective classifications of mammographic parenchyma (Spearman correlation coefficients, Rs = -0.88 and -0.76 for skewness and fractal dimension measurements, respectively). Further, neither measure was strongly dependent on simulated changes in mammographic technique. Correlation with subjective classification of mammographic density was better when both the skewness and fractal measures were used in combination than when either was used alone. This suggests that each feature provides some independent information.
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Cited by
Warner, E., Plewes, D. B., Shumak, R. S., Catzavelos, G. C., Di Prospero, L. S., Yaffe, M. J., Goel, V., Ramsay, E., Chart, P. L., Cole, D. E. C., et al. (2001) · Journal of Clinical Oncology · doi:10.1200/jco.2001.19.15.3524 · Cited by 461
Self-citationA review of automatic mass detection and segmentation in mammographic images
Oliver, A., Freixenet, J., Martí, J., Pérez, E., Pont, J., Denton, E. R. E., & Zwiggelaar, R. (2010) · Medical Image Analysis · doi:10.1016/j.media.2009.12.005 · Cited by 398
Quantifying tumour heterogeneity with CT
Ganeshan, B., & Miles, K. A. (2013) · Cancer Imaging · doi:10.1102/1470-7330.2013.0015 · Cited by 395
A review of computer-aided diagnosis of breast cancer: Toward the detection of subtle signs
Rangayyan, R. M., Ayres, F. J., & Leo Desautels, J. E. (2007) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2006.09.003 · Cited by 337
Giger, M. L., Chan, H., & Boone, J. (2008) · Medical Physics · doi:10.1118/1.3013555 · Cited by 311
Metadata
- Authors
- Byng, J. W., Boyd, N. F., Fishell, E., Jong, R. A., & Yaffe, M. J.
- Venue
- Physics in Medicine and Biology
- Publisher
- IOP Publishing
- Published
- 1996-05-01
- Volume
- 41
- Issue
- 5
- Pages
- 909-923
- ISSN
- 0031-9155 (ISSN-L)
- 1361-6560
- OpenAlex
- W2150242770
- Cited by
- 208
- References
- 0
- FWCI
- 4.06
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Byng, J. W., Boyd, N. F., Fishell, E., Jong, R. A., & Yaffe, M. J. (1996). Automated analysis of mammographic densities. Physics in Medicine and Biology. https://doi.org/10.1088/0031-9155/41/5/007
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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